Intracranial Dural Arteriovenous Fistulas with Pial Arterial Supply
Bibliographic record
Abstract
BACKGROUND: Pial arterial supplies are sometimes found in patients with dural arteriovenous fistulas (DAVFs), though their characteristics have rarely been clarified. OBJECTIVE: To investigate the characteristics of pial arterial supplies in DAVFs and to discuss their pathophysiology and treatment. METHODS: Two hundred four consecutive patients with intracranial DAVFs over 11 yr were retrospectively reviewed. Clinical factors and radiological findings, including the presence of pial arterial supplies, were evaluated. Supply from a pial artery was classified into 2 categories: dilated pre-existing dural branches of pial arteries, and a "pure" pial supply. RESULTS: Twenty-three of 204 patients (11.3%) showed an additional pial arterial supply. Multivariate analysis identified 3 independent predictors of a pial arterial supply: younger age (P < .0005), DAVF within the tentorium (P = .0162), and presence of venous dilatation (P = .0001). A dilated pre-existing dural branch of a pial artery was identified in 17 patients, while 8 had a pure pial supply. Of these 23 patients, 17 underwent interventional therapy. No postoperative intracranial hemorrhage or infarction occurred in patients with pial arterial supplies. CONCLUSION: An additional pial supply is not uncommon in DAVFs and may be explained by a rich physiological pial arterial supply to the dura mater from the posterior circulation, while potential angiogenesis due to venous hypertension remains speculative. Prior to interventional treatment for DAVFs, recognition of a pial arterial supply to the DAVF might influence the treatment strategy and could help avoid inadvertent retrograde embolization of brain supplying vessels through the pial network.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".